Paper Info
Title
The Effects of Normalisation on the Ability of Business End-Users to Detect Data Anomalies: An Experimental Evaluation
Abstract
With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.
Year
Venue
Keywords
2001
JOURNAL OF RESEARCH AND PRACTICE IN INFORMATION TECHNOLOGY
end-user queries,data quality,normalisation
DocType
Volume
Issue
Journal
33
3
ISSN
Citations 
PageRank 
1443-458X
0
0.34
References 
Authors
2
4
Name
Order
Citations
PageRank
A. Faye Borthick17210.68
Paul L. Bowen221120.98
M. R. Liu300.34
Fiona H. Rohde415813.42